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Objectives To determine the diagnostic accuracy of ultra-high-resolution photon-counting detector CT angiography (UHR PCD-CTA) for evaluating coronary stent patency compared to invasive coronary angiography (ICA). Methods Consecutive, clinically referred patients with prior coronary stent implantation were prospectively enrolled between August 2022 and March 2023 and underwent UHR PCD-CTA (collimation, 120 × 0.2 mm). Two radiologists independently analyzed image quality of the in-stent lumen using a 5-point Likert scale, ranging from 1 (“excellent”) to 5 (“non-diagnostic”), and assessed all coronary stents for the presence of in-stent stenosis (≥ 50% lumen narrowing). The diagnostic accuracy of UHR PCD-CTA was determined, with ICA serving as the standard of reference. Results A total of 44 coronary stents in 18 participants (mean age, 83 years ± 6 [standard deviation]; 12 women) were included in the analysis. In 3/44 stents, both readers described image quality as non-diagnostic, whereas reader 2 noted a fourth stent to have non-diagnostic image quality. In comparison to ICA, UHR PCD-CTA demonstrated a sensitivity, specificity, and accuracy of 100% (95% CI [confidence interval] 47.8, 100), 92.3% (95% CI 79.1, 98.4), and 93.2% (95% CI 81.3, 98.6) for reader 1 and 100% (95% CI 47.8, 100), 87.2% (95% CI 72.6, 95.7), and 88.6% (95% CI 75.4, 96.2) for reader 2, respectively. Both readers observed a 100% negative predictive value (36/36 stents and 34/34 stents). Stent patency inter-reader agreement was 90.1%, corresponding to a substantial Cohen’s kappa value of 0.72. Conclusions UHR PCD-CTA enables non-invasive assessment of coronary stent patency with high image quality and diagnostic accuracy. Clinical relevance statement Ultra-high-resolution photon-counting detector CT angiography represents a reliable and non-invasive method for assessing coronary stent patency. Its high negative predictive value makes it a promising alternative over invasive coronary angiography for the rule-out of in-stent stenosis. Key Points • CT-based evaluation of coronary stent patency is limited by stent-induced artifacts and spatial resolution. • Ultra-high-resolution photon-counting detector CT accurately evaluates coronary stent patency compared to invasive coronary angiography. • Photon-counting detector CT represents a promising method for the non-invasive rule-out of in-stent stenosis.

Objectives Computed tomography (CT) is employed to evaluate surgical outcome after spinal interventions. Here, we investigate the potential of multispectral photon-counting computed tomography (PC-CT) on image quality, diagnostic confidence, and radiation dose compared to an energy-integrating CT (EID-CT). Methods In this prospective study, 32 patients underwent PC-CT of the spine. Data was reconstructed in two ways: (1) standard bone kernel with 65-keV (PC-CT std ) and (2) 130-keV monoenergetic images (PC-CT 130 keV ). Prior EID-CT was available for 17 patients; for the remaining 15, an age–, sex–, and body mass index–matched EID-CT cohort was identified. Image quality (5-point Likert scales on overall, sharpness, artifacts, noise, diagnostic confidence) of PC-CT std and EID-CT was assessed by four radiologists independently. If metallic implants were present ( n  = 10), PC-CT std and PC-CT 130 keV images were again assessed by 5-point Likert scales by the same radiologists. Hounsfield units (HU) were measured within metallic artifact and compared between PC-CT std and PC-CT 130 keV . Finally, the radiation dose (CTDI vol ) was evaluated. Results Sharpness was rated significantly higher ( p  = 0.009) and noise significantly lower ( p  < 0.001) in PC-CTstd vs. EID-CT. In the subset of patients with metallic implants, reading scores for PC-CT 130 keV revealed superior ratings vs. PC-CT std for image quality, artifacts, noise, and diagnostic confidence (all p  < 0.001) accompanied by a significant increase of HU values within the artifact ( p  < 0.001). Radiation dose was significantly lower for PC-CT vs. EID-CT (mean CTDI vol : 8.83 vs. 15.7 mGy; p  < 0.001). Conclusions PC-CT of the spine with high-kiloelectronvolt reconstructions provides sharper images, higher diagnostic confidence, and lower radiation dose in patients with metallic implants. Key Points • Compared to energy-integrating CT, photon-counting CT of the spine had significantly higher sharpness and lower image noise while radiation dose was reduced by 45%. • In patients with metallic implants, virtual monochromatic photon-counting images at 130 keV were superior to standard reconstruction at 65 keV in terms of image quality, artifacts, noise, and diagnostic confidence.

Accurate small vessel stent visualization using CT remains challenging. Photon-counting CT (PCD-CT) may help to overcome this issue. We systematically investigate PCD-CT impact on small vessel stent assessment compared to energy-integrating-CT (EID). 12 water-contrast agent filled stents (3.0–8 mm) were scanned with patient-equivalent phantom using clinical PCD-CT and EID-CT. Images were reconstructed using dedicated vascular kernels. Subjective image quality was evaluated by 5 radiologists independently (5-point Likert-scale; 5 = excellent). Objective image quality was evaluated by calculating multi-row intensity profiles including edge rise slope (ERS) and coefficient-of-variation (CV). Highest overall reading scores were found for PCD-CT-Bv56 (3.6[3.3–4.3]). In pairwise comparison, differences were significant for PCD-CT-Bv56 vs. EID-CT-Bv40 ( p  ≤ 0.04), for sharpness and blooming respectively (all p  < 0.05). Highest diagnostic confidence was found for PCD-CT-Bv56 ( p  ≤ 0.2). ANOVA revealed a significant effect of kernel strength on ERS ( p  < 0.001). CV decreased with stronger PCD-CT kernels, reaching its lowest in PCD-CT-Bv56 and highest in EID-CT reconstruction ( p  ≤ 0.05). We are the first study to verify, by phantom setup adapted to real patient settings, PCD-CT with a sharp vascular kernel provides the most favorable image quality for small vessel stent imaging. PCD-CT may reduce the number of invasive coronary angiograms, however, more studies needed to apply our results in clinical practice.

Differentiation of incidental adrenal lesions remains a challenge in diagnostic imaging, especially on single-phase portal venous computed tomography (CT) in the oncological setting. The aim of the study was to explore the ability of dual-energy CT (DECT)-based iodine quantification and virtual non-contrast (VNC) imaging and advanced radiomic analysis of DECT for differentiation of adrenal adenomas from metastases. A total of 46 patients with 49 adrenal lesions underwent clinically indicated staging DECT and magnetic resonance imaging. Median values of quantitative parameters such as VNC, fat fraction, and iodine density in DECT images were collected and compared between adenomas and metastases using non-parametric tests. Magnetic resonance imaging, washout CT, and clinical follow-up were used as a reference standard. Diagnostic accuracy was assessed by calculating receiver operating characteristics. A DECT tumor analysis prototype software was used for semiautomatic segmentation of adrenal lesions and extraction of radiomic features. A radiomics prototype was used to analyze the data with multiple logistic regression and random forest classification to determine the area under the curve (AUC). The study cohort (60.87% women; mean age: 66.91 [+ or -] 12.93 years) consisted of 32 adenomas and 17 metastases. DECT-based VNC imaging (AUC = 0.89) and fat quantification (AUC = 0.86) differentiate between adrenal adenomas and metastases with high diagnostic accuracy (P < .001). Analysis of radiomic features revealed that DECT features such as VNC imaging and fat fraction (AUC = 0.87-0.89; < .001) and radiomic features such as 90th percentile and total energy (AUC = 0.88-0.93; P < .001) differentiate with high diagnostic accuracy between adrenal adenomas and metastases. Random forest classification revealed an AUC of 0.83 for separating adrenal adenomas from metastases. Virtual non-contrast imaging and fat quantification as well as extraction of radiomic features accurately differentiate between adrenal adenomas and metastases on single-phase oncologic staging DECT.

Computed tomography (CT) is an established method for the diagnosis, staging, and treatment of multiple myeloma. Here, we investigated the potential of photon-counting detector computed tomography (PCD-CT) in terms of image quality, diagnostic confidence, and radiation dose compared with energy-integrating detector CT (EID-CT). In this prospective study, patients with known multiple myeloma underwent clinically indicated whole-body PCD-CT. The image quality of PCD-CT was assessed qualitatively by three independent radiologists for overall image quality, edge sharpness, image noise, lesion conspicuity, and diagnostic confidence using a 5-point Likert scale (5 = excellent), and quantitatively for signal homogeneity using the coefficient of variation (CV) of Hounsfield Units (HU) values and modulation transfer function (MTF) via the full width at half maximum (FWHM) in the frequency space. The results were compared with those of the current clinical standard EID-CT protocols as controls. Additionally, the radiation dose (CTDI ) was determined. We enrolled 35 patients with multiple myeloma (mean age 69.8 ± 9.1 years; 18 [51%] males). Qualitative image analysis revealed superior scores (median [interquartile range]) for PCD-CT regarding overall image quality (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), edge sharpness (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), image noise (4.0 [4.0-4.0] vs. 3.0 [3.0-4.0]), lesion conspicuity (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]), and diagnostic confidence (4.0 [4.0-5.0] vs. 4.0 [3.0-4.0]) compared with EID-CT ( ≤ 0.004). In quantitative image analyses, PCD-CT compared with EID-CT revealed a substantially lower FWHM (2.89 vs. 25.68 cy/pixel) and a significantly more homogeneous signal (mean CV ± standard deviation [SD], 0.99 ± 0.65 vs. 1.66 ± 0.5; < 0.001) at a significantly lower radiation dose (mean CTDI ± SD, 3.33 ± 0.82 vs. 7.19 ± 3.57 mGy; < 0.001). Whole-body PCD-CT provides significantly higher subjective and objective image quality at significantly reduced radiation doses than the current clinical standard EID-CT protocols, along with readily available multi-spectral data, facilitating the potential for further advanced post-processing.

BackgroundTo assess the additive value of dual-energy CT (DECT) over single-energy CT (SECT) to radiomics-based response prediction in patients with metastatic melanoma preceding immunotherapy.Material and methodsA total of 140 consecutive patients with melanoma (58 female, 63±16 years) for whom baseline DECT tumor load assessment revealed stage IV and who were subsequently treated with immunotherapy were included. Best response was determined using the clinical reports (81 responders: 27 complete response, 45 partial response, 9 stable disease). Individual lesion response was classified manually analogous to RECIST 1.1 through 1291 follow-up examinations on a total of 776 lesions (6.7±7.2 per patient). The patients were sorted chronologically into a study and a validation cohort (each n=70). The baseline DECT was examined using specialized tumor segmentation prototype software, and radiomic features were analyzed for response predictors. Significant features were selected using univariate statistics with Bonferroni correction and multiple logistic regression. The area under the receiver operating characteristic curve of the best subset was computed (AUROC). For each combination (SECT/DECT and patient response/lesion response), an individual random forest classifier with 10-fold internal cross-validation was trained on the study cohort and tested on the validation cohort to confirm the predictive performance.ResultsWe performed manual RECIST 1.1 response analysis on a total of 6533 lesions. Multivariate statistics selected significant features for patient response in SECT (min. brightness, R²=0.112, padj. ≤0.001) and DECT (textural coarseness, R²=0.121, padj. ≤0.001), as well as lesion response in SECT (mean absolute voxel intensity deviation, R²=0.115, padj. ≤0.001) and DECT (iodine uptake metrics, R²≥0.12, padj. ≤0.001). Applying the machine learning models to the validation cohort confirmed the additive predictive power of DECT (patient response AUROC SECT=0.5, DECT=0.75; lesion response AUROC SECT=0.61, DECT=0.85; p<0.001).ConclusionThe new method of DECT-specific radiomic analysis provides a significant additive value over SECT radiomics approaches for response prediction in patients with metastatic melanoma preceding immunotherapy, especially on a lesion-based level. As mixed tumor response is not uncommon in metastatic melanoma, this lends a powerful tool for clinical decision-making and may potentially be an essential step toward individualized medicine.

Background Gunshot deaths due to homicide or military encounters are a major health concern. Noninvasive bullet characterization is of major importance for patients with lodged bullets or in mass disasters with multiple cadavers, which must be prioritized for autopsy. Therefore, the aim of this study was to investigate whether brass and lead bullets can be differentiated using photon-counting CT (PCCT). Methods Nine different lead ( n  = 6) or brass ( n  = 3) bullets were investigated on a state-of-the-art PCCT using a clinically unavailable research mode. Here, four image sets were reconstructed for different energy thresholds (20, 55, 72, 90 keV). Three circular regions of interest were placed on the 20-keV threshold images by two readers and automatically copied to the three other threshold images. Based on measured HU mean and max values, dual-energy indices (DEI) were calculated for the low/high energy threshold pairs of 20/90, 55/90, and 72/90 keV. Results Significant differences of DEIs between lead and brass projectiles were observed for the 20/90 keV DEI for HU mean ± standard deviation values (Qr40 kernel, lead: -0.085 ± 0.021, brass: 0.024 ± 0.048) and HU max values (Qr40 kernel, lead: -0.093 ± 0.011, brass: 0.023 ± 0.057) ( p  < 0.001 for both). Differences decreased for the 55/90 and 72/90 keV DEIs between the two projectile materials but remained statistically significant. Conclusion In this PCCT phantom study, significant differences were observed between lead and brass bullets in the different energy threshold images. Relevance statement Photon-counting CT could be a promising tool for bullet identification as significant differences were found in the different energy threshold images for lead and brass bullets, with application in clinical and forensic radiology. Key Points In emergency settings, noninvasive bullet characterization is of importance for law enforcement. Bullet material characterization can be performed using photon-counting CT. These characteristics can be quantified in the four different energy threshold images. Graphical Abstract

Background To assess the potential of virtual monoenergetic images (VMIs) on a photon-counting computed tomography (PCCT) for reducing the amount of injected iodine contrast media compared to an energy-integrating CT (EICT). Methods A multienergy phantom was scanned with a PCCT and EICT at 11 mGy with abdomen-pelvis examination parameters. VMIs were generated at 40 keV, 50 keV, 60 keV, and 70 keV. For all VMIs, the contrast-to-noise ratio (CNR) of iodine inserts with concentrations of 1 mg/mL, 2 mg/mL, 5 mg/mL, 10 mg/mL, and 15 mg/mL was calculated by dividing the signal difference between HU in iodine inserts versus solid water by the noise value assessed on solid water. The potential reduction in iodine media was calculated by the rate of reduction in iodine concentration with PCCT while maintaining the same CNR obtained with EICT for the reference concentration. Results Significantly higher CNR values were found with PCCT at all VMI energy levels for iodine concentrations above 1 mg/mL. The highest reduction was observed at 40 keV, with a value of 48.9 ± 1.6% (mean ± standard deviation). It decreased as the energy level increased, by 38.5 ± 0.5%, and 30.8 ± 0.8% for 50 and 60 keV, respectively. For 70 keV, the potential reduction of 24.4 ± 1.1% was found for iodine concentrations above 1 mg/mL. This reduction reached 57 ± 2.3% at 40 keV with PCCT compared to 60 keV with EICT. Conclusion For abdomen-pelvis protocols, the use of VMIs with PCCT significantly improved the CNR of iodine, offering the potential to reduce the required contrast medium. Relevance statement The use of VMIs with PCCT may reduce the quantity of iodine contrast medium to be injected compared with EICT, limiting costs, the risk of adverse effects, and the amount of contrast agent released into the wastewater. Key Points PCCT improves the image quality of VMIs. PCCT offers the potential for reducing the amount of injected contrast medium. PCCT potential for reducing the injected contrast medium depends on energy level. Graphical Abstract

The aim was to evaluate the accuracy of a prototypical artificial intelligence-based algorithm for automated segmentation and diameter measurement of the thoracic aorta (TA) using CT. One hundred twenty-two patients who underwent dual-source CT were retrospectively included. Ninety-three of these patients had been administered intravenous iodinated contrast. Images were evaluated using the prototypical algorithm, which segments the TA and determines the corresponding diameters at predefined anatomical locations based on the American Heart Association guidelines. The reference standard was established by two radiologists individually in a blinded, randomized fashion. Equivalency was tested and inter-reader agreement was assessed using intra-class correlation (ICC). In total, 99.2% of the parameters measured by the prototype were assessable. In nine patients, the prototype failed to determine one diameter along the vessel. Measurements along the TA did not differ between the algorithm and readers (p > 0.05), establishing equivalence. Inter-reader agreement between the algorithm and readers (ICC ≥ 0.961; 95% CI: 0.940–0.974), and between the readers was excellent (ICC ≥ 0.879; 95% CI: 0.818–0.92). The evaluated prototypical AI-based algorithm accurately measured TA diameters at each region of interest independent of the use of either contrast utilization or pathology. This indicates that the prototypical algorithm has substantial potential as a valuable tool in the rapid clinical evaluation of aortic pathology.

The aim of this phantom study was to assess the detectability and volumetric accuracy of pulmonary nodules on photon-counting detector CT (PCD-CT) at different low-dose levels compared to conventional energy-integrating detector CT (EID-CT). In-house fabricated artificial nodules of different shapes (spherical, lobulated, spiculated), sizes (2.5–10 mm and 5–1222 mm3), and densities (−330 HU and 100 HU) were randomly inserted into an anthropomorphic thorax phantom. The phantom was scanned with a low-dose chest protocol with PCD-CT and EID-CT, in which the dose with PCD-CT was lowered from 100% to 10% with respect to the EID-CT reference dose. Two blinded observers independently assessed the CT examinations of the nodules. A third observer measured the nodule volumes using commercial software. The influence of the scanner type, dose, observer, physical nodule volume, shape, and density on the detectability and volumetric accuracy was assessed by a multivariable regression analysis. In 120 CT examinations, 642 nodules were present. Observer 1 and 2 detected 367 (57%) and 289 nodules (45%), respectively. With PCD-CT and EID-CT, the nodule detectability was similar. The physical nodule volumes were underestimated by 20% (range 8–52%) with PCD-CT and 24% (range 9–52%) with EID-CT. With PCD-CT, no significant decrease in the detectability and volumetric accuracy was found at dose reductions down to 10% of the reference dose (p > 0.05). The detectability and volumetric accuracy were significantly influenced by the observer, nodule volume, and a spiculated nodule shape (p < 0.05), but not by dose, CT scanner type, and nodule density (p > 0.05). Low-dose PCD-CT demonstrates potential to detect and assess the volumes of pulmonary nodules, even with a radiation dose reduction of up to 90%.